The invention relates generally to the field of power systems, including single- and multi-converter power systems and in particular to monitoring, detecting and/or diagnosing one or more faults in such power converter systems.
Present methods and systems for monitoring, detecting and/or diagnosing fault make use of systems and methods requiring very large knowledge base and/or involving weights to match fault types. Such methods include neural networks, fuzzy logic, genetic algorithm, expert systems, optimization and wavelet, as examples, and are computationally intensive. Most require large memory allocation and often do not provide fast real time fault diagnosis without allowing some damage to first occur to the system. Thus, while more suitable for post fault analysis, existing methods are unable to indicate the type or the nature of the fault. Accordingly, there remains a need to provide improved vehicles, devices, systems and methods for monitoring, detecting and/or diagnosing fault.